| Autor: |
Neha Gupta, Arun Sharma, Manoj Kumar Pachariya |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 6, Pp 2897-2909 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1319-1578 |
| DOI: |
10.1016/j.jksuci.2020.01.009 |
| Popis: |
Testing of software is done with an intention to find faults. If a fault is there then it needs to be detected, located and then resolved. Fault detection and localization are adjoining activities and thus it is difficult to combine them. Fault detection requires test information that helps in detecting the faults early whereas fault localization requires information which helps in locating the faults accurately. But test information is one common thing that is required for both the activities. This pre-condition helps to effectively combine both fault detection and localization. In this research work, a code and mutant coverage based multi-objective approach has been proposed to produce a minimized test suite having the ability of both detecting and locating faults. For optimization of test cases, NSGA-II algorithm has been used. Results on the projects of Defects4j repository depicts that the proposed approach is able to produce minimized test suites having the capability of detecting 95.16% of faults and locating all detected faults with fault localization score almost equivalent to that of the complete test suite. The average percentage of reduction in test suite size is 78% which is a good reduction percentage with the given fault detection and localization scores. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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